Triple
T31788600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Björkarnas stad |
E811399
|
entity |
| Predicate | usedAsNicknameIn |
P13305
|
FINISHED |
| Object | Sweden |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Sweden | Statement: [Björkarnas stad, usedAsNicknameIn, Sweden]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsNicknameIn Context triple: [Björkarnas stad, usedAsNicknameIn, Sweden]
-
A.
usesNicknameIn
Indicates that one entity refers to another entity by a specific nickname within a particular context or setting.
-
B.
usedAsNicknameSince
Indicates that one entity has been used as a nickname for another entity starting from a specified point in time.
-
C.
usesNicknameOf
Indicates that one entity refers to another entity by a nickname derived from or associated with that other entity’s name.
-
D.
usesNicknameFor
Indicates that one entity habitually refers to another entity by a nickname rather than their formal or given name.
-
E.
nameUsedIn
chosen
Indicates that a particular name is employed or referenced within a specified context, work, or usage setting.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f348e60748819082dcaa7792659803 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd76d1e5208190a6f26651492d1e3c |
completed | May 8, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69fd702a226c81908edfda00f4be4130 |
completed | May 8, 2026, 5:10 a.m. |
Created at: April 30, 2026, 11:38 p.m.